Reviving The Health Revolution » Vocabularies

Understanding Components of CCD

vaibhavb — Thu, 28 Jan 2010 01:52:35 +0000

Connectivity of Care Document (CCD) is a collaborative standard driven by HL7 & ASTM for exchanging summary format clinical information.

For ease of understanding one can think of CCD standard comprising of several elements in an hierarchical fashion:

HL7 V3 Data Types and Reference Information Model (RIM) : At the base of CCD standard are the HL7 Data types and Reference Information Model. HL7 V3 data types define the structural format of the data carried. The HL7 RIM expresses the information content of work done by HL7 working committee to define data types, relationships between them, and a state transition model for some entities.
Clinical Document Architecture (CDA): The HL7 CDA defines the specific structure and semantics for any clinical document for purposes of exchange. CDA document can be encoded in XML. A CDA document if encoded in XML must comply to the schema. NIST has a good CDA validation tool.
CCD Implementation Guide: The CCD implementation guide describes the constraints on the HL7 Clinical Document Architecture R2 specification in accordance with requirements set forward by ASTM (the governing body behind CCR).

Fig 1. Components of CCD Standard

Understanding CCR

vaibhavb — Tue, 27 Oct 2009 22:27:50 +0000

Update: Fixed typos, added links to related tools and articles, updated the example.

CCR or Continuity of Care Record is a standard meant to ease the exchange of clinical information with a relatively easy to read and practical data-format and schema. There is ton of great information about CCR on its resource site. CCR document format is supported by majority of personal Health clouds, both – Microsoft HealthVault & Google Health.

The CCR specification comprises an implementation guide, XML schema definition and a guidance spreadsheet for each data element that makes up the standard. These resources can be bought from ASTM.

The document format of CCR is very straight forward, consisting of a header, body and a footer with the following top-level elements:

Header	Body	Body	Footer
CCR Document ID Language Version Creation Date Patient From To Purpose	Payers Advance Directives Support Functional Status Problems Family History Social History Alerts Medications	Medical Equipment Immunizations Vital Signs Results Procedures Encounters Plan Of Care HealthCareProviders	Actors Signatures References Comments

Google Health supports only a limited set of entities from the above, while HealthVault supports the entire standard and also allows transformation of some of these entities in to native HealthVault types. You can read more about working with CCR in HealthVault and various input mappings, output mappings, and CCR vocabularies.

Here are some illustrative CCR figures from Dr. Waldren’s presentation (see end of article).

Using the SNOMED-CT concepts one can write the Systolic Blood pressure reading in CCR as the following (UPDATE: Well-formatted the CCR to include source, object-id and actors, thanks to Matt Wagner):

xml version="1.0" encoding="utf-8"?>
<ContinuityOfCareRecord xmlns='urn:astm-org:CCR'>
  <CCRDocumentObjectID>DocCCRDocumentObjectID>
  <Language>
    <Text>EnglishText>
  Language>
  <Version>V1.0Version>
  <DateTime>
    <ExactDateTime>2008ExactDateTime>
  DateTime>
  <Patient>
    <ActorID>PatientActorID>
  Patient>
  <Body>
    <VitalSigns>
      <Result>
        <CCRDataObjectID>0001CCRDataObjectID>
        <Description>
          <Text>Blood PressureText>
        Description>
        <Source>
          <Description>
            <Text>UnknownText>
          Description>
        Source>
        <Test>
          <CCRDataObjectID>0002CCRDataObjectID>
          <Description>
            <Text>SystolicText>
            <Code>
              <Value>163030003Value>
              <CodingSystem>SNOMEDCTCodingSystem>
            Code>
          Description>
          <Source>
            <Description>
              <Text>UnknownText>
            Description>
          Source>
          <TestResult>
            <Value>120Value>
            <Units>
              <Unit>mmHgUnit>
            Units>
          TestResult>
        Test>
        <Test>
          <CCRDataObjectID>0003CCRDataObjectID>
          <Description>
            <Text>DiastolicText>
            <Code>
              <Value>163031004Value>
              <CodingSystem>SNOMEDCTCodingSystem>
            Code>
          Description>
          <Source>
            <Description>
              <Text>UnknownText>
            Description>
          Source>
          <TestResult>
            <Value>75Value>
            <Units>
              <Unit>mmHgUnit>
            Units>
          TestResult>
        Test>
      Result>
    VitalSigns>
  Body>
  <Actors>
    <Actor>
      <ActorObjectID>PatientActorObjectID>
      <Person>
        <Name>
          <CurrentName>
            <Given>JohnGiven>
            <Family>DoeFamily>
          CurrentName>
        Name>
      Person>
      <Source>
        <Description>
          <Text>UnknownText>
        Description>
      Source>
    Actor>
  Actors>
ContinuityOfCareRecord>

Note CodingSystem element. It allows CCR to interpret various medical vocabularies.

Relevant Tools:

(Thanks to Kathleen Connor)

The CCR Validator, is an important resource to test/validate a CCR instance, is a now available Not only does it validate the CCR against the XSD but also the constraints of the implementation guide.
An Open Source StyleSheet to view CCR files.
CCR to CCD & HL7 Mappers – tools which Map CCR to CCD and HL7 V2 & V3. You can access them directly here.
Application to embed CCR in PDF-HealthCare.

Related Article(s):

To get familiar with CCR I would highly recommended this 13 minute video by Dr. Steve Waldren.
Adam Bosworth posted an interesting read on standards, his take (simple, human readable, focus on known structured data, etc.) favors CCR.

In this series:

Special thanks to Kathy Osborne for proof reading this post.

Understanding SNOMED CT

vaibhavb — Fri, 09 Oct 2009 22:11:00 +0000

I have previously posted about Understanding Health Ontologies and Standards. In this post I’ll focus on SNOMED-CT (Systematized Nomenclature of Medicine Clinical Terms). SNOMED-CT is the most comprehensive vocabulary to express clinical terms – it spans languages, specialties and geographic borders.

SNOMED-CT includes:

Terms or synonyms relating to a clinical concept
Links between different concepts

To give you a taste here is an example of Blood pressure reading represented using SNOMED-CT from the linked paper (“Towards semantic interoperability in healthcare: ontology mapping from SNOMED-CT to HL7 version 3”, Amanda Ryan):

In addition to having a model to represent concepts and linkages the biggest draw of SNOMED CT is a staggering number of coded qualifiers (which belong to one concept or other). According to IHTSO there are about 311,000 actively used SNOMED CT concepts.

You can register for SNOMED CT here. Its free for companies and individuals in United States, however your registration is processed by NLM and it might take over 3 days to receive a confirmation and access.

Once you are through with registration and have an account, start by downloading the core subset of SNOMED CT concepts here, this list consists of about 5000 most frequently used terms by institutions across US. Its a good set to get familiar with, it consists of the following concept area:

Clinical finding : 4,550 codes in total
Procedure : 414 codes in total
Situation with explicit context : 132 codes in total
Event : 38 codes in total
Body structure : 46 codes in total
Social context : 2 codes in total

We can use BCP to copy the files from SNOMED CT Core in to our local database, and do more interesting queries & data analysis like find distribution on these terms, co-relate problems vs. findings and of course work on the larger SNOMED CT database to find synonyms etc.; but I’ll keep that for another day. Here very quickly I’ll show how one can use a web-based browser, Snowflake, http://snomed.dataline.co.uk/ (requires registration) to lookup a SNOMED code and see what else it relates to. We can see that in line 3 above SNOMED CT concept 10085004 is marked as Metatarsalgia (finding), however using the Snowflake browser we can see in that in addition to being a finding this concept is a problem as well.

This was just tip of the ice-berg, please leave comments for future posts / areas to consider in the Ontology domain.

Understanding Vocabularies #2 – HealthVault Recommendations

vaibhavb — Sat, 11 Jul 2009 01:46:50 +0000

In my last article in the vocabulary category, I described the need for semantically enabled data and how different categories of health data have different standard vocabulary / ontology associated with them. In the following table I attempt to summarize the recommended vocabularies for different HealthVault types.

Disclaimer: Please note this is not a definitive or complete list, and I will update the table as I discover inconsistencies. The definitive source are the XSDs associated with HealthVault data types.

HealthVault Type	Type Schema	HV Recommended vocabulary related to this type	Comments
Advance Directive	822a5e5a-14f1-4d06-b92f-8f3f1b05218f	None	Examples include living wills and power of attorney for healthcare.
Allergy	52bf9104-2c5e-4f1f-a66d-552ebcc53df7	icd9cm, icd9cm-reactions	Details on ICD-9 Codes
Basic Demographic Information	bf516a61-5252-4c28-a979-27f45f62f78d	ISO-3166	Country of residence
Blood Glucose Measurement	879e7c04-4e8a-4707-9ad3-b054df467ce4	glucose-measurement-type
Blood Oxygen Saturation	3a54f95f-03d8-4f62-815f-f691fc94a500	blood-oxygen-saturation-measurement-method
Body Composition	18adc276-5144-4e7e-bf6c-e56d8250adf8	body-composition-measurement-methods
Body Dimension	dd710b31-2b6f-45bd-9552-253562b9a7c1	body-dimension-measurement-names, body-dimension-measurement-names-pediatric
Calorie Guideline	d3170d30-a41b-4bde-a116-87698c8a001a	calorie-guideline-names
Concern	aea2e8f2-11dd-4a7d-ab43-1d58764ebc19	concern-description	Concerns are more general than conditions
Condition	7ea7a1f9-880b-4bd4-b593-f5660f20eda8
Continuity of Care Document (CCD)	9c48a2b8-952c-4f5a-935d-f3292326bf54
Continuity of Care Record (CCR)	1e1ccbfc-a55d-4d91-8940-fa2fbf73c195		http://www.ccrstandard.com/
Daily Medication Usage	a9a76456-0357-493e-b840-598bbb9483fd	dose-purpose, usage-schedule, x12-de-1330, prescription-type, x12-d3-355,
Diabetes Insulin Injection Use	184166be-8adb-4d9c-8162-c403040e31ad	insulin-types,
Discharge Summary	02ef57a2-a620-425a-8e92-a301542cca54	icd9cm
HbA1C Measurement	227f55fb-1001-4d4e-9f6a-8d893e07b451	HbA1C-assay-method
Health Assessment	58fd8ac4-6c47-41a3-94b2-478401f0e26c	health-assessment-name, health-assessment-value-sets, health-assessment-groups, health-assessment-category
Heart Rate	b81eb4a6-6eac-4292-ae93-3872d6870994	heart-rate-measurement-conditions
HL7 Clinical Document Architecture, Release 2	1ed1cba6-9530-44a3-b7b5-e8219690ebcf
Immunization	cd3587b5-b6e1-4565-ab3b-1c3ad45eb04f	vaccines-cvx, vaccine-manufacturers-mvx, medication-routes,
Insulin Injection	3b3c053b-b1fe-4e11-9e22-d4b480de74e8	insulin-types
Insurance Plan	9366440c-ec81-4b89-b231-308a4c4d70ed	coverage-types
Lab Test Results	f57746af-9631-49dc-944e-2c92bee0d1e9	LOINC, lab-status, lab-results-flag,	More on LOINC here.
Medication	30cafccc-047d-4288-94ef-643571f7919d	Rxnorm, NDC, medication-prescribed
Medication Fill	167ecf6b-bb54-43f9-a473-507b334907e0	Rxnorm, NDC
Personal Demographic Information	92ba621e-66b3-4a01-bd73-74844aed4f5b	blood-types, ethnicity, marital-status, religion, education-level,
Pregnancy	46d485cf-2b84-429d-9159-83152ba801f4	delivery-complications, anesthesia-methods, delivery-methods, pregnancy-outcomes, gender-types, conception-methods,
Question Answer	55d33791-58de-4cae-8c78-819e12ba5059	question-sets, answer-choice-sets
Sleep Related Activity	031f5706-7f1a-11db-ad56-7bd355d89593		November 2005, "Your Guide to Healthy Sleep", ISBN 1-933236-05-1
Sleep Session	11c52484-7f1a-11db-aeac-87d355d89593		November 2005, "Your Guide to Healthy Sleep", ISBN 1-933236-05-1
Vital Signs	73822612-c15f-4b49-9e65-6af369e55c65	lab-results-units, lab-results-flag,

As you can notice above we recommend ICD-9, RxNorm, LOINC, NDC. x12-de-1130, x12-de-335. We do prefer SNOMED-CT as well, however the application using it need to have license for it.

Having written the above I would like to match that with what Dr. Halamka recommends in his post. Note that I mention content column for completeness, however its not useful for comparison.

Data	Content	Vocabulary
Demographics	HL7 2.x for messaging, CCD for document summaries	HITSP Harmonized code sets for gender, marital status
Problem List	HL7 2.x for messaging, CCD for document summaries	SNOMED-CT
Medications	NCPDP script for messaging, CCD for document summaries	RxNorm and Structured SIG
Allergies	HL7 2.x for messaging, CCD for document summaries	UNII for foods and substances, NDF-RT for medication class, RxNorm for Medications
Progress Notes and Other Narrative Documents (History and Physical, Operative Notes, Discharge Summary)	HL7 2.x for messaging, CCD for document summaries	CDA Templates (interesting note)
Departmental Reports (Pathology/Cytology, GI, Pulmonary, Cardiology etc.)	HL7 2.x for messaging, CCD for document summaries	SNOMED-CT
Laboratory Results	HL7 2.x for messaging, CCD for document summaries	LOINC for lab name, UCUM for units of measure, SNOMED-CT for test ordering reason
Microbiology	HL7 2.x for messaging, CCD for document summaries	LOINC for lab name/observation
Images	DICOM
Administrative Transactions (Benefits/Eligibility, Referral/Authorization, Claims/Remittance)	X12	X12, CAQH CORE

Next Time: I’ll try to update the above tables with more details and try to come with recommendations of which clinical type (in the Data column above) would potentially match with which HealthVault type.

As usual leave your suggestions in the comments.

Understanding Vocabularies. Wait! What did you say?

vaibhavb — Thu, 09 Apr 2009 19:22:14 +0000

Any data system the semantic meaning of data is as important as the strucutre of the data. In HealthVault we expose a very structured data set in form of various data types and the semantic meaning of the content in those data sets is dictated by vocabularies.

HealthVault Vocabulary is a big area so I’m going to attempt to break this down in separate series of posts. In this post i’m primarily going to focus on vocabularies in general.

Many of you might have heard of the term – Semantic Web or Web 3.0. So whats this buzz about? Well Web 1.0 was for humans to connect, Web 2.0 was for systems to connect to humans via rich internet applications. Web 3.0 promises a web for systems – a web where programs can communicate and link to each other. So what this implies is for Semantic Web to be successful – the data being put on the semantic internet need not only be structured but also the content be in such a way that computer programs can understand the meaning of it. This is only possible if everyone has a shared Vocabulary or Ontology, or a mechanism to relate to a new Vocabulary.

To solve the ontology problem we can just sit down and invent a vocabulary which everyone will use henceforth and be done with it, right! First, we won’t agree to single vocabulary and second we can’t plan for future vocabularies. And the most important challenge is that the system which powers this vocabulary needs to agree with the architecture of the web i.e must be decentralized and open!

The semantic web community is using a very powerful way to achieve this. They are using the same mechanism which powers resource discovery (for example – URL linking) to discover and understand vocabularies. Two candidates which make this possible are RDF (resource description format) and OWL (Web Ontology Language). I won’t describe these technologies in details here but keep it for some other day. However the point of this note is to surface example ontologies or vocabularies this community has successfully used/developed so far:

FOAF – http://en.wikipedia.org/wiki/FOAF_(software) : This ontology describes a persons social network
FAO – http://en.wikipedia.org/wiki/Geopolitical_ontology: This ontology describes a geopolitical unit.

So how does this fit in the HealthCare? John Hamalka outlines the elements of vocabulary whicn an EHR can use in his post – http://geekdoctor.blogspot.com/2009/04/data-elements-of-ehr.html. He mentions preferred vocabularies and transports for some of important EHR elements. In the following posts i will try to go deeper in this area.

So how does this fit with HealthVault? Well HealthVault exposes all the vocabularies it uses – http://developer.healthvault.com/types/vocabs.aspx. We let people also annotate their data with any vocabulary they like. However this leds to an interesting interoperability problem, so on the XSD schemas of our data types (http://developer.healthvault.com/types/types.aspx) we specify preferred vocabularies for some data elements. In the following posts i will provide more details with regards to this.

As you can from John’s post their is no dearth of language systems for various medical or healthcare terms. However their is a big gap on best practices on how one can denormalize various vocabularies for implementeting systems which can interoperate with other systems using different vocabularies. I tend to think that there are some lessons to be learned in this area from semantic web efforts and also a need for a more structured effort to surface best practices. May be I’ll dig deeper in this area in one of the future posts.

Next post: Recommended Vocabularies for Various Data Contexts.

Semantic Web Glossary (semanticalley.com)
Semantic web – The foundations (digital-constructions.com)
A conference comes of age: a review of the 7th International Semantic Web Conference (ISWC2008) (blogs.talis.com)